We have just completed a major People Analytics study and the results are striking. Only 10% of companies directly correlate human capital data to operations in a systemic way, with numerous data, technical and operational challenges. Yet, as our research has revealed, AI is poised to completely change this market. Here is the story.
Early in my career, I attended HR analytics conferences and found analysts working hard and doing amazing things, wondering why no one was listening to them. Now, 25 years later, these people continue to do incredible work, but are still frustrated in their progress.
Here’s the problem: Companies are short on talent. Despite the impending automation of AI, every organization is scrambling to find new skills, hire frontline workers, and fill its leadership pipeline as baby boomers retire. Healthcare workers will be short 2 million clinicians over the next three years; retailers and manufacturers face similar challenges.
As these workforce challenges loom, we are now inundated with data to help. Companies use platforms like Eightfold, LinkedIn, Lightcast and Draup to identify talent, identify salary needs and find critical skills with laser precision. In theory, then, we should have HR analytics as powerful as any CRM or financial planning system.
Well, no. After billions spent on HCM platforms, less than 10% of companies can directly correlate or link HR and people data to business metrics. And that’s a problem.
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I just read last week that Salesforce was going to hire 1,000 new salespeople to sell their AI agents. (A strange move: hiring salespeople to sell a system that eliminates the need for salespeople.). Mark Benioff, a wise leader, would probably like to know exactly what skills these 1,000 people need, what training they need, and how many of them can be redeployed internally. Does he have this information? I doubt it.
This is the problem everywhere. We spend billions on HR software, but the People Analytics team is often required to run scientific projects to understand retention, skills gaps, or other important but internal issues. How many companies can measure and monitor human capital with the rigor they demonstrate in their supply chain, financial operations or customer retention?
THE the answer is about 10%. In a sense, this is progress: the last time we conducted this study, this figure was much lower. But it’s not high enough. Given that payroll is the company’s largest discretionary expense, shouldn’t we be measuring the impact on people with laser precision? Of course we should do it, it’s very difficult to do.
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Why is it so difficult? For several reasons.
- First, data is scattered all over employee systems (most companies have 30 to 40 human resources and productivity systems).
- Second, the data is not clearly defined, so it takes a lot of effort to determine the actual retention rate when there are seasonal variations, family changes, and many other factors.
- Third, we have very little correlation between business systems and HR systems.
Consider the promise of ERP. The reason we bought Workday, SAP, Oracle, or another ERP was to bring this data together. Well, it’s on one “platform”, but the vendors haven’t been very good at providing us with out-of-the-box correlations. Try writing a simple report: “sales results correlate to years of experience”. I bet it takes you a week even to get the right data. So no sales manager will ever try.
Things are about to change, and quickly.
Like our new research highlightsPeople Analytics is one of the “last mature areas of HR.” And that’s for the reasons above, plus the fact that some companies just don’t think about “being data-centric” enough.
Enter AI: the most integrated, systemic, and easy-to-use data management technology we’ve ever seen.
I remember when SQL was a pioneer: we spent millions on tools like Business Objects, MicroStrategy, and Essbase. We built data warehouses and data extraction tools. We hired data scientists and built predictive models. Well, AI can do almost all of that for us, with an interface that doesn’t require a PhD to work.
I’m not saying that managing HR and HCM data is easy: it’s not. But with new tools like Visier, Workday Illuminate, SAP Joule, OneModel, CruncHR and Galileo, this whole area is about to change.
Imagine if you “threw” your sales per employee data into Galileo, then “threw” into the database employee history, compensation data, and training history. If you label the data correctly, AI will immediately allow you to ask “what is the relationship between turnover and seniority, training history, span of managerial control and salary?” You will get a good answer. (I did this in Galileo.)
The AI may not know that some salespeople have plum territories and others don’t, and it also may not know that some sales leaders are great and others are problematic. But you will quickly get the basic information and then you can “add” this other data to improve the answer.
I’m not kidding. I’ve been doing data analysis and management for over 30 years and these new tools are as revolutionary as the spreadsheet was compared to an HP calculator.
OUR research explains it all in detailand also shows you how internal skills, culture and practices such as consulting, storytelling and business partnership are also necessary. For the first time in my career, we can get out of our offices and spend less time cleaning data, building models, extracting data, and creating graphs. Let AI do this for us.
Besides, this is all very new. New AI tools like Visier’s Vee, Galileo, Joule, Illuminate and others are barely a year old. But they are moving at the speed of light. Your new job is to manage data (Corpus) and spend more time understanding the big problems to work on.
We call this “Systemic analysis» – looking at the “system”, not just an isolated part. What role does recruitment play in turnover? A lot. What role does work schedule play in productivity? A lot. Every human capital factor is linked – and there are hundreds of variables to consider. Once we’ve gathered all this data into an easy-to-use system, we can ask AI to show us what’s happening.
Bring People Analytics to the C-Suite
Here’s a simple question: At the end of the quarter, look at what your CEO and CFO are talking about. Something like “revenues were 6% lower than expected in the United States, but 8% higher in Asia.”
Wouldn’t you like to know what the human problems are behind this variation? AI will allow us to answer this question. So, every quarter, the CEO can declare “our employee productivity increased by 11% in Asia, thanks to new hiring practices and the compensation model we implemented.”
The 10% of companies that do this deserve a lot of credit. As our research detailsthese companies are hiring HR business people, giving them consulting roles, and equipping them with data tools to dig deep. And yes, they suffer from the same data quality issues as others, but they solve them.
They define People Analytics as a Business Analysis function, not a doctoral group to study psychology. These questions are also important, but they are only contributors and not where the big actions are happening. And they understand HR topics such as retention, engagement, leadership, and skills pathways in detail. And they get a huge reward.
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I can’t wait to tell you where this is going. Get your hand on Galileojoin us at the Visier User Conference, or join our corporate membership (fully powered by AI now, Galileo included) and you will see how you can boost your human capital operations.
Additional Information
Certificate Course in People Analytics at the Josh Bersin Academy
Systemic analysis: a new approach
Galileo, the AI assistant for everything HR-related
